Simultaneous placement and scheduling of sensors

We consider the problem of monitoring spatial phenomena, such as road speeds on a highway, using wireless sensors with limited battery life. A central question is to decide where to locate these sensors to best predict the phenomenon at the unsensed locations. However, given the power constraints, w...

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Bibliographic Details
Published in:2009 International Conference on Information Processing in Sensor Networks pp. 181 - 192
Main Authors: Krause, Andreas, Rajagopal, Ram, Gupta, Anupam, Guestrin, Carlos
Format: Conference Proceeding
Language:English
Published: Washington, DC, USA IEEE Computer Society 13.04.2009
IEEE
Series:ACM Conferences
Subjects:
Accuracy
Approximation algorithms
Batteries
Computer systems organization > Dependable and fault-tolerant systems and networks
General and reference > Cross-computing tools and techniques > Performance
Mathematics of computing > Mathematical analysis > Functional analysis > Approximation
Mathematics of computing > Mathematical analysis > Mathematical optimization
Monitoring
Networks > Network performance evaluation
Networks > Network services > Network management
Processor scheduling
Road transportation
Scheduling algorithm
Sensor networks
Sensor phenomena and characterization
Telecommunication traffic
Theory of computation > Design and analysis of algorithms > Approximation algorithms analysis
Theory of computation > Design and analysis of algorithms > Approximation algorithms analysis > Scheduling algorithms
Theory of computation > Design and analysis of algorithms > Mathematical optimization
Theory of computation > Design and analysis of algorithms > Online algorithms > Online learning algorithms > Scheduling algorithms
Theory of computation > Theory and algorithms for application domains > Machine learning theory > Reinforcement learning > Sequential decision making
Wireless sensor networks
ISBN:1424451086, 9781424451081
Online Access:Get full text
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Summary:We consider the problem of monitoring spatial phenomena, such as road speeds on a highway, using wireless sensors with limited battery life. A central question is to decide where to locate these sensors to best predict the phenomenon at the unsensed locations. However, given the power constraints, we also need to determine when to selectively activate these sensors in order to maximize the performance while satisfying lifetime requirements. Traditionally, these two problems of sensor placement and scheduling have been considered separately from each other; one first decides where to place the sensors, and then when to activate them. In this paper, we present an efficient algorithm, ESPASS, that simultaneously optimizes the placement and the schedule. We prove that ESPASS provides a constant-factor approximation to the optimal solution of this NP-hard optimization problem. A salient feature of our approach is that it obtains “balanced” schedules that perform uniformly well over time, rather than only on average. We then extend the algorithm to allow for a smooth power-accuracy tradeoff. Our algorithm applies to complex settings where the sensing quality of a set of sensors is measured, e.g., in the improvement of prediction accuracy (more formally, to situations where the sensing quality function is submodular). We present extensive empirical studies on several sensing tasks, and our results show that simultaneously placing and scheduling gives drastically improved performance compared to separate placement and scheduling (e.g., a 33% improvement in network lifetime on the traffic prediction task).
ISBN:1424451086
9781424451081
DOI:10.5555/1602165.1602183